Perception and Regulatory Principles of Microbial Growth Control

Fast growth represents an effective strategy for microbial organisms to survive in competitive environments. To accomplish this task, cells must adapt their metabolism to changing nutrient conditions in a way that maximizes their growth rate. However, the regulation of the growth related metabolic pathways can be fundamentally different among microbes. We therefore asked whether growth control by perception of the cell’s intracellular metabolic state can give rise to higher growth than by direct perception of extracellular nutrient availability. To answer this question, we created a simplified dynamical computer model of a cellular metabolic network whose regulation was inferred by an optimization approach. We used this model for a competing species experiment, where a species with extracellular nutrient perception competes against one with intracellular nutrient perception by evaluating their respective average growth rate. We found that the intracellular perception is advantageous under situations where the up and down regulation of pathways cannot follow the fast changing nutrient availability in the environment. In this case, optimal regulation ignores any other nutrients except the most preferential ones, in agreement with the phenomenon of catabolite repression in prokaryotes. The corresponding metabolic pathways remain activated, despite environmental fluctuations. Therefore, the cell can take up preferential nutrients as soon as they are available without any prior regulation. As a result species that rely on intracellular perception gain a relevant fitness advantage in fluctuating nutrient environments, which enables survival by outgrowing competitors.     

Dynamic Proteomic Characteristics and Network Integration Revealing Key Proteins for Two Kernel Tissue Developments in Popcorn

The formation and development of maize kernel is a complex dynamic physiological and biochemical process that involves the temporal and spatial expression of many proteins and the regulation of metabolic pathways. In this study, the protein profiles of the endosperm and pericarp at three important developmental stages were analyzed by isobaric tags for relative and absolute quantification (iTRAQ) labeling coupled with LC-MS/MS in popcorn inbred N04. Comparative quantitative proteomic analyses among developmental stages and between tissues were performed, and the protein networks were integrated. A total of 6,876 proteins were identified, of which 1,396 were nonredundant. Specific proteins and different expression patterns were observed across developmental stages and tissues. The functional annotation of the identified proteins revealed the importance of metabolic and cellular processes, and binding and catalytic activities for the development of the tissues. The whole, endosperm-specific and pericarp-specific protein networks integrated 125, 9 and 77 proteins, respectively, which were involved in 54 KEGG pathways and reflected their complex metabolic interactions. Confirmation for the iTRAQ endosperm proteins by two-dimensional gel electrophoresis showed that 44.44% proteins were commonly found. However, the concordance between mRNA level and the protein abundance varied across different proteins, stages, tissues and inbred lines, according to the gene cloning and expression analyses of four relevant proteins with important functions and different expression levels. But the result by western blot showed their same expression tendency for the four proteins as by iTRAQ. These results could provide new insights into the developmental mechanisms of endosperm and pericarp, and grain formation in maize.     

Thermodynamically based profiling of drug metabolism and drug-drug metabolic interactions: a case study of acetaminophen and ethanol toxic interaction

Drug-drug metabolic interactions can result in unwanted side effects, including reduced drug efficacy and formation of toxic metabolic intermediates. In this work, thermodynamic constraints on non-equilibrium metabolite concentrations are used to reveal the biochemical interactions between the metabolic pathways of ethanol and acetaminophen (N-acetyl-p-aminophenol), two drugs known to interact unfavorably. It is known that many reactions of these pathways are coupled to the central energy metabolic reactions through a number of metabolites and the cellular redox potential. Based on these observations, a metabolic network model has been constructed and a database of thermodynamic properties for all participating metabolites and reactions has been compiled. Constraint-based computational analysis of the feasible metabolite concentrations reveals that the non-toxic pathways for APAP metabolism and the pathway for detoxifying N-acetyl-p-benzoquinoneimine (NAPQI) are inhibited by network interactions with ethanol metabolism. These results point to the potential utility of thermodynamically based profiling of metabolic network interactions in screening of drug candidates and analysis of potential toxicity.     

Hierarchical analysis of dependency in metabolic networks

MOTIVATION: Elucidation of metabolic networks for an increasing number of organisms reveals that even small networks can contain thousands of reactions and chemical species. The intimate connectivity between components complicates their decomposition into biologically meaningful sub-networks. Moreover, traditional higher-order representations of metabolic networks as metabolic pathways, suffers from the lack of rigorous definition, yielding pathways of disparate content and size. RESULTS: We introduce a hierarchical representation that emphasizes the gross organization of metabolic networks in largely independent pathways and sub-systems at several levels of independence. The approach highlights the coupling of different pathways and the shared compounds responsible for those couplings. By assessing our results on Escherichia coli (E.coli metabolic reactions, Genetic Circuits Research Group, University of California, San Diego, http://gcrg.ucsd.edu/organisms/ecoli.html, 'model v 1.01. reactions') against accepted biochemical annotations, we provide the first systematic synopsis of an organism's metabolism. Comparison with operons of E.coli shows that low-level clusters are reflected in genome organization and gene regulation. AVAILABILITY: Source code, data sets and supplementary information are available at http://www.mas.ecp.fr/labo/equipe/gagneur/hierarchy/hierarchy.html     

Estimation of Gibbs energy changes of central metabolism reactions

Changes in Gibbs energies of metabolic reactions of glycolysis and Krebs cycle have been calculated from literature data including G, pK values, and complex formation constants values. Neutral, charged species and Mg-complexes are included in the data base. Results show that most of the reactions investigated proceed near thermodynamic equilibrium conditions whereas the reactions out of equilibrium are related to the metabolic regulation and seem associated with cyclic sequences or with parallel pathways. Examples of fructose 6-phosphate/fructose 1,6-diphosphate cycle and phosphotranferase system and hexokinase are presented.     

Mitochondrial respiratory control in the myocardium

The heart muscle has proved to be a practical model for studying respiratory control in intact tissues. It also demonstrates that control at the level of the respiratory chain is augmented by metabolic control at the substrate level as exemplified by the very narrow range of changes in the redox state of the mitochondrial NADH/NAD couple even during extensive changes in ATP and oxygen consumption. The behaviour of mitochondria when isolated can largely be duplicated in the intact myocardium. Moreover, the high intracellular concentrations of enzymes, coenzymes and adenine nucleotides create conditions of high reaction rates, enabling the formation of a near equilibrium network of certain main pathways. This equilibrium network in connection with metabolic regulation of the hydrogen pressure upon the matrix NADH/NAD pool is a prerequisite for the regulation of cellular respiration at a high efficiency of energy transfer. Experimentation on the intact myocardium also seems to be capable of resolving some of the uncertainties about prevailing mechanisms for the regulation of cellular respiration.     

Cytokine regulation in experimentally-induced Schistosoma japonicum egg granuloma formation

The formation of granulomas in host tissues in response to trapped Schistosoma japonicum eggs is central to the etiology of schistosomiasis. However, analysis of the host hypersensitivity reactions that result in granuloma formation, in schistosome infection, is not without difficulty. This is due, in part, to the fact that the parasites continuously deposit their eggs as clusters. In order to synchronize host reactions, we established an experimental model of hepatic granuloma formation whereby in vitro laid schistosome eggs are implanted directly into normal and cytokine-deficient mice livers. This model, validated by comparison with an infection model, was used to analyze cytokine regulation of granuloma formation around S. japonicum eggs. Combined models of implantation and cercarial infection were also studied. With special reference to IL-4, IL-13, IFN-γ and IL-18, our in vitro schistosome egg implantation model has shed new light on the roles of cytokines in both the acute and chronic stages of schistosome egg-induced granuloma formation.     

Thermodynamics-based metabolic flux analysis

A new form of metabolic flux analysis (MFA) called thermodynamics-based metabolic flux analysis (TMFA) is introduced with the capability of generating thermodynamically feasible flux and metabolite activity profiles on a genome scale. TMFA involves the use of a set of linear thermodynamic constraints in addition to the mass balance constraints typically used in MFA. TMFA produces flux distributions that do not contain any thermodynamically infeasible reactions or pathways, and it provides information about the free energy change of reactions and the range of metabolite activities in addition to reaction fluxes. TMFA is applied to study the thermodynamically feasible ranges for the fluxes and the Gibbs free energy change, Delta(r)G', of the reactions and the activities of the metabolites in the genome-scale metabolic model of Escherichia coli developed by Palsson and co-workers. In the TMFA of the genome scale model, the metabolite activities and reaction Delta(r)G' are able to achieve a wide range of values at optimal growth. The reaction dihydroorotase is identified as a possible thermodynamic bottleneck in E. coli metabolism with a Delta(r)G' constrained close to zero while numerous reactions are identified throughout metabolism for which Delta(r)G' is always highly negative regardless of metabolite concentrations. As it has been proposed previously, these reactions with exclusively negative Delta(r)G' might be candidates for cell regulation, and we find that a significant number of these reactions appear to be the first steps in the linear portion of numerous biosynthesis pathways. The thermodynamically feasible ranges for the concentration ratios ATP/ADP, NAD(P)/NAD(P)H, and H(extracellular)(+)/H(intracellular)(+) are also determined and found to encompass the values observed experimentally in every case. Further, we find that the NAD/NADH and NADP/NADPH ratios maintained in the cell are close to the minimum feasible ratio and maximum feasible ratio, respectively.     

The biosynthesis of monolignols: a "metabolic grid", or independent pathways to guaiacyl and syringyl units?

Lignin is a complex polymer formed by the oxidative polymerization of hydroxycinnamyl alcohol derivatives termed monolignols. The major monolignols in dicotyledonous angiosperm lignin are monomethylated guaiacyl (G) units derived from coniferyl alcohol, and dimethylated syringyl (S) units derived from sinapyl alcohol. The biochemical pathways leading to the formation of monolignols feature successive hydroxylation and O-methylation of the aromatic ring and conversion of the side chain carboxyl to an alcohol function. The current view of the monolignol biosynthetic pathway envisages a metabolic grid leading to G and S units, through which the successive hydroxylation and O-methylation reactions may occur at different levels of side chain oxidation. The present article assesses biochemical and genetic evidence for and against such a model, including recent data on the methylation reactions of monolignol biosynthesis in alfalfa. We draw attention to portions of the currently accepted monolignol pathway that may require revision, and suggest an alternative model in which metabolic channeling allows for independent pathways to G and S lignin.     

Genome-scale metabolic model for Lactococcus lactis MG1363 and its application to the analysis of flavor formation

Lactococcus lactis subsp. cremoris MG1363 is a paradigm strain for lactococci used in industrial dairy fermentations. However, despite of its importance for process development, no genome-scale metabolic model has been reported thus far. Moreover, current models for other lactococci only focus on growth and sugar degradation. A metabolic model that includes nitrogen metabolism and flavor-forming pathways is instrumental for the understanding and designing new industrial applications of these lactic acid bacteria. A genome-scale, constraint-based model of the metabolism and transport in L. lactis MG1363, accounting for 518 genes, 754 reactions, and 650 metabolites, was developed and experimentally validated. Fifty-nine reactions are directly or indirectly involved in flavor formation. Flux Balance Analysis and Flux Variability Analysis were used to investigate flux distributions within the whole metabolic network. Anaerobic carbon-limited continuous cultures were used for estimating the energetic parameters. A thorough model-driven analysis showing a highly flexible nitrogen metabolism, e.g., branched-chain amino acid catabolism which coupled with the redox balance, is pivotal for the prediction of the formation of different flavor compounds. Furthermore, the model predicted the formation of volatile sulfur compounds as a result of the fermentation. These products were subsequently identified in the experimental fermentations carried out. Thus, the genome-scale metabolic model couples the carbon and nitrogen metabolism in L. lactis MG1363 with complete known catabolic pathways leading to flavor formation. The model provided valuable insights into the metabolic networks underlying flavor formation and has the potential to contribute to new developments in dairy industries and cheese-flavor research.     

Reappraisal of the currently prevailing model of starch biosynthesis in photosynthetic tissues: a proposal involving the cytosolic production of ADP-glucose by sucrose synthase and occurrence of cyclic turnover of starch in the chloroplast.

A vast amount of information has accumulated which supports the view that sucrose and starch are end-products of two segregated, yet highly interconnected, gluconeogenic pathways taking place in the cytosol and chloroplast, respectively. However, several lines of experimental evidences indicate that, essentially identical to the case of heterotrophic tissues, starch formation in the photosynthetic tissues may involve the direct import to the chloroplast of cytosolic hexose (C6) units derived from the sucrose breakdown. This evidence is consistent with the idea that synthesis of a sizable pool of ADP-glucose takes place in the cytosol by means of sucrose synthase whereas, basically in agreement with recent investigations dealing with glycogen biosynthesis in bacteria and animals, chloroplastic phosphoglucomutase and ADP-glucose pyrophosphorylase are most likely playing a role in channelling of glucose units derived from the starch breakdown in the chloroplast, thus making up a regulatory starch turnover cycle. According to this new view, we propose that starch production in the chloroplast is the result of a flexible and dynamic mechanism wherein both catabolic and anabolic reactions take place simultaneously in a highly interactive manner. Starch is seen as an intermediate component of a cyclic gluconeogenic pathway which, in turn, is connected with other metabolic pathways. The possible importance of metabolic turnover as a way to control starch production is exemplified with the recently discovered ADP-glucose pyrophosphatase, an enzyme likely having a dual role in controlling levels of ADP-glucose linked to starch biosynthesis and diverting carbon flow towards other metabolic pathways.     

Analysis of growth of Lactobacillus plantarum WCFS1 on a complex medium using a genome-scale metabolic model

A genome-scale metabolic model of the lactic acid bacterium Lactobacillus plantarum WCFS1 was constructed based on genomic content and experimental data. The complete model includes 721 genes, 643 reactions, and 531 metabolites. Different stoichiometric modeling techniques were used for interpretation of complex fermentation data, as L. plantarum is adapted to nutrient-rich environments and only grows in media supplemented with vitamins and amino acids. (i) Based on experimental input and output fluxes, maximal ATP production was estimated and related to growth rate. (ii) Optimization of ATP production further identified amino acid catabolic pathways that were not previously associated with free-energy metabolism. (iii) Genome-scale elementary flux mode analysis identified 28 potential futile cycles. (iv) Flux variability analysis supplemented the elementary mode analysis in identifying parallel pathways, e.g. pathways with identical end products but different co-factor usage. Strongly increased flexibility in the metabolic network was observed when strict coupling between catabolic ATP production and anabolic consumption was relaxed. These results illustrate how a genome-scale metabolic model and associated constraint-based modeling techniques can be used to analyze the physiology of growth on a complex medium rather than a minimal salts medium. However, optimization of biomass formation using the Flux Balance Analysis approach, reported to successfully predict growth rate and by product formation in Escherichia coli and Saccharomyces cerevisiae, predicted too high biomass yields that were incompatible with the observed lactate production. The reason is that this approach assumes optimal efficiency of substrate to biomass conversion, and can therefore not predict the metabolically inefficient lactate formation.     

Carbonyl Stress in Bacteria: Causes and Consequences

Pathways of synthesis of the α-reactive carbonyl compound methylglyoxal (MG) in prokaryotes are described in this review. Accumulation of MG leads to development of carbonyl stress. Some pathways of MG formation are similar for both pro- and eukaryotes, but there are reactions specific for prokaryotes, e.g. the methylglyoxal synthase reaction. This reaction and the glyoxalase system constitute an alternative pathway of glucose catabolism–the MG shunt not associated with the synthesis of ATP. In violation of the regulation of metabolism, the cell uses MG shunt as well as other glycolysis shunting pathways and futile cycles enabling stabilization of its energetic status. MG was first examined as a biologically active metabolic factor participating in the formation of phenotypic polymorphism and hyperpersistent potential of bacterial populations. The study of carbonyl stress is interesting for evolutionary biology and can be useful for constructing highly effective producer strains.     

MRAD: Metabolic reaction analysis database--an entity-relationship approach

The Metabolic Reaction Analysis Database (MRAD) is a relational database based on the Entity-Relationship (ER) model which combines information about organisms, biochemical pathways, reactions, enzymes, substrates, products and genes. It describes 244,596 genes in 79 organisms, 6,552 enzymes, and 3,552 reactions, 3,100 substrates, 2,866 products and 118 metabolic pathways. The MRAD graphical user interface allows for the identification of metabolic reactions which are similar and dissimilar in multiple organisms, reactions in a pathway which are missing in an organism and using any combination between one to six of the biological entities of organisms, genes, pathways, enzymes, substrates and products to determine metabolic reactions. MRAD provides a powerful and efficient tool for the construction of flux balance models for metabolic engineering applications.